Microenvironment and Metastasis in Breast and Gynecological Tumors

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Immunology and Immunotherapy".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 394

Special Issue Editors


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Guest Editor
Division of Pathology, IEO, European Institute of Oncology IRCCS, Via Giuseppe Ripamonti 435, 20141 Milan, Italy
Interests: translational research; breast cancer; biomarkers; immunology; molecular biology; TILs; precision medicine

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Guest Editor
Department of Public Health, University of Naples Federico II, Naples, Italy
Interests: precision medicine; translation research; gynecological malignancies; molecular biomarkers; liquid biopsy; solid tumors; ICIs; next-generation sequencing

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Guest Editor
Department of Medicine, Division of Hematology-Oncology, Weill Cornell Medicine, New York, NY 10021, USA
Interests: liquid biopsy; circulating tumor cells; circulating tumor DNA; breast cancer

Special Issue Information

Dear Colleagues,

Breast and gynecological cancers represent a significant health burden globally, affecting millions of women each year. Despite advances in diagnosis and treatment, metastasis remains the primary cause of mortality in these malignancies. The tumor microenvironment plays a pivotal role in orchestrating cancer progression, influencing cellular behaviors, therapeutic responses and disease outcomes. Understanding the intricate interplay between tumor cells and their surrounding milieu is crucial for developing novel therapeutic strategies to combat metastatic dissemination. In this context, exploring the role of biomarkers can further increase our understanding in targeting metastasis in breast and gynecological cancers.

This Special Issue of Cancers aims to explore the complex dynamics of the tumor microenvironment in breast and gynecological tumors, shedding light on the molecular and cellular mechanisms driving metastasis.

Authors are welcome to submit comprehensive review articles, original research studies and communications of preliminary, but significant, experimental results. Each submitted manuscript will undergo a formal peer review process. Submitted manuscripts must not have been published previously, nor can they be under consideration for publication in other journals.

Dr. Konstantinos Venetis
Dr. Francesco Pepe
Dr. Carolina Reduzzi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • breast cancer
  • gynecological tumors
  • tumor microenvironment
  • immune modulation
  • metastasis
  • cellular interactions
  • stromal components
  • biomarkers

Published Papers (1 paper)

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Review

21 pages, 993 KiB  
Review
Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence
by Mariia Ivanova, Carlo Pescia, Dario Trapani, Konstantinos Venetis, Chiara Frascarelli, Eltjona Mane, Giulia Cursano, Elham Sajjadi, Cristian Scatena, Bruna Cerbelli, Giulia d’Amati, Francesca Maria Porta, Elena Guerini-Rocco, Carmen Criscitiello, Giuseppe Curigliano and Nicola Fusco
Cancers 2024, 16(11), 1981; https://doi.org/10.3390/cancers16111981 - 23 May 2024
Viewed by 276
Abstract
Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine [...] Read more.
Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep learning, and convolutional neural networks, AI is reshaping predictive algorithms for recurrence risk, thereby revolutionizing diagnostic accuracy and treatment planning. Beyond detection, AI applications extend to histological subtyping, grading, lymph node assessment, and molecular feature identification, fostering personalized therapy decisions. With rising cancer rates, it is crucial to implement AI to accelerate breakthroughs in clinical practice, benefiting both patients and healthcare providers. However, it is important to recognize that while AI offers powerful automation and analysis tools, it lacks the nuanced understanding, clinical context, and ethical considerations inherent to human pathologists in patient care. Hence, the successful integration of AI into clinical practice demands collaborative efforts between medical experts and computational pathologists to optimize patient outcomes. Full article
(This article belongs to the Special Issue Microenvironment and Metastasis in Breast and Gynecological Tumors)
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